CN111300984A - Parameter self-tuning method for roll printing system and roll printing system - Google Patents
Parameter self-tuning method for roll printing system and roll printing system Download PDFInfo
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Abstract
The invention discloses a parameter self-tuning method for a roll printing system and the roll printing system, wherein the method comprises the steps of performing closed-loop identification and low-frequency correction by using a pseudorandom signal in the closed-loop operation process of the roll printing system so as to obtain a high-order mathematical model after low-frequency correction; and then, obtaining disturbance distribution information by using the model, carrying out spectrum analysis on the disturbance distribution information to obtain a disturbance spectrum, and then carrying out controller parameter setting according to the disturbance spectrum and the model, wherein the set controller parameters meet the requirements of the anti-interference capability and the stability of the system. The invention solves the problems of high performance requirement, large change of system characteristics and high order of the roll printing system, and ensures that the system can meet the requirements of stability, tracking performance and anti-interference performance under different roll loads.
Description
Technical Field
The invention relates to the technical field of servo control, in particular to a parameter self-tuning method for a roll printing system and the roll printing system.
Background
In a roll plate printing machine system, a motor and a load are generally connected through transmission mechanisms such as a transmission shaft, a gear or a coupling, and due to the fact that the rigidity of the transmission mechanisms is limited, the load inertia is large, and flexible transmission exists between the motor and the load, mechanical resonance exists in the system, and the system always has the characteristic of more than three orders. The roll plate serving as the load needs to be replaced frequently, and the inertia, the form and the installation and connection conditions of the roll plate are different every time, so that the overall characteristics of a controlled object of the system are changed greatly after the roll plate is replaced, and the overall characteristics comprise system gain, mechanical resonance and the like. In this case, the original controller parameters may not be able to meet the performance requirements of the new object, even causing instability due to large variations in object characteristics. In such a background, the self-tuning of the controller becomes a problem that has to be solved in engineering practice.
At present, commercial parameter self-tuning is divided into rule-based parameter self-tuning and model-based parameter self-tuning, and the rule-based parameter self-tuning is difficult to make, and unreasonable setting can cause overlong convergence time and generally poorer unstable effect, and large calculation amount is difficult to realize. The model-based parameter self-tuning depends on the accuracy of a mathematical model, most of the model identification algorithms in the current commercial controller are sweep frequency identification and step identification, the former has long operation time and large calculation amount, and the latter can only obtain a model below the second order generally and is not suitable for a system with higher system order and medium-high frequency resonance. For example, the latest series driver of mitsubishi has functions of identifying rotational inertia and self-tuning parameters, and the latest series driver firstly identifies load rotational inertia through an acceleration and deceleration process and then uses an empirical formula to tune related parameters according to the load rotational inertia and mechanical rigidity set by a user, and the method is not suitable for a high-order system with mechanical resonance drift, such as a roll-to-roll printing machine.
In addition, in practical engineering applications, conditions for applying an open-loop identification method are often not met, the process to be identified is in a closed-loop control environment, and due to considerations in terms of production safety and system reliability, the process to be identified is not allowed to be switched from a closed-loop operation to an open-loop operation, and therefore, the closed-loop identification is very important when model-based parameter self-setting is performed.
Disclosure of Invention
The first purpose of the invention is to overcome the defects of the prior art and provide a parameter self-tuning method for a roll printing system, which can solve the problems of high performance requirement, large system characteristic change and high order of the roll printing system and is suitable for the roll printing system.
A second object of the present invention is to provide a pad printing system that meets the requirements of stability, tracking and interference resistance under different pad loads.
It is a third object of the invention to provide a computing device.
The first purpose of the invention is realized by the following technical scheme: a parameter self-tuning method for a roll printing system comprises the following steps:
in the closed-loop operation process of the roll printing system, performing closed-loop identification and low-frequency correction by using a pseudorandom signal so as to obtain a high-order mathematical model after low-frequency correction;
obtaining disturbance distribution information by using the operation data and the model of the system and carrying out spectrum analysis on the disturbance distribution information to obtain a disturbance spectrum;
and (4) setting the controller parameters according to the disturbance frequency spectrum and the model, wherein the set controller parameters meet the requirements of the anti-interference capability and the stability of the system.
Preferably, the process of performing closed-loop identification and low-frequency correction using the pseudo-random signal to obtain a low-frequency corrected higher-order mathematical model is as follows:
(1) a conservative controller is used for enabling the system to be in a closed-loop operation state, or a gain self-adjusting controller is used for obtaining a stable but slightly conservative controller, so that the system stably operates to a stable state;
(2) giving a pseudorandom excitation signal with a fixed length to a controllable input point close to an object to be identified in a loop, transmitting a superposed signal to the input of the object to be identified, and then acquiring input data and output data of the object to be identified according to a sampling period until the excitation of the pseudorandom signal is finished;
(3) judging whether the upper limit of the frequency of the interference signal can be estimated or not, if not, performing data fusion on the steady-state data and the object input and output data, and identifying to obtain a high-order model after low-frequency correction;
if yes, obtaining an identification model capable of describing characteristics of each frequency band of the system through input and output data, and then carrying out low-frequency correction on the identification model to obtain a high-order mathematical model after low-frequency correction.
Furthermore, the object to be identified is a part of the system from the controller output end to the controller input end; the input and output data u of the object to be identified are superposed with the pseudo-random excitation signalr(t)、yr(t)。
Further, the steady state data is the steady state value u input and output by the object to be identified when the system is operated to the steady state in the step (1)svAnd ysv；
Performing data fusion on the steady-state data and the input and output data of the object to be identified, and identifying to obtain a high-order model after low-frequency correction, wherein the method specifically comprises the following steps:
will usvAnd ur(t) fusing to obtain u (t), and fusing ysvAnd yr(t) fusing to obtain y (t) such that:
u(jw)|w＝0＝usv；
u(jw)|w≠0＝ur(jw)；
y(jw)|w＝0＝ysv；
y(jw)|w≠0＝yr(jw)；
wherein u (jw), ur(jw)、y(jw)、yr(jw) are u (t), u, respectivelyr(t)、yr(t), y (t) Fourier frequency domain transform;
then, u (t), y (t) and u (t) obtained by fusion are used for identification.
Further, the obtaining of the identification model specifically includes: and obtaining an n-order model transfer function G(s) by using a least square method or a subspace method according to the input and output data.
Further, the low frequency correction is performed on the identification model, which is as follows:
(1) according to the input and output data u of the object to be identified in the steady statesv、ysvTo obtain the steady state gain of the system
(2) Low frequency separation is performed on the nth order model transfer function g(s) to reduce the amount of computation: g(s) ═ Gl(s)Gh(s) in which Gl(s) is the low frequency characteristic part of the system, Gh(s) is a system high frequency characteristic part;
(3) then solve the following:
Gl'(0)＝K；
min|Gl'(jw)-Gl(jw)|,w>wh；
wherein w is a frequency variable, Gl'(0)＝Gl'(s)|s＝0，Gl(jw)＝Gl(s)|s＝jw，Gl'(jw)＝Gl'(s)|s＝jwRefers to the frequency response, w, of the modelhEstimating the upper limit of the low-frequency interference frequency;
obtaining G from the above formulal'(s) to obtain a corrected model G'(s) ═ Gl'(s)Gh(s)。
Preferably, the parameter setting of the controller is performed according to the disturbance spectrum and the model, and the process is as follows:
(1) acquiring loop data in operation in a stable operation stage, and acquiring a stable stage interference estimation signal d (t) according to a controller and a model G'(s);
(2) carrying out frequency domain transformation on the interference signal, determining frequency distribution and interference principal components, and obtaining an anti-interference capability index according to a performance index gamma and an interference channel model S:
|S(jw)d(jw)|<γ；
wherein S (jw) is the frequency response of interference channel S, S (jw) is S (S) non-volatile memorys＝jwD (jw) is the Fourier frequency domain transform of d (t);
(3) solving the corresponding parameters of the controller by using a loop forming method so as to:
wherein L (jw) is the system open loop transfer function,
for phase margin, Gm(. cndot.) is the margin of amplitude,
to expect amplitude margin, GrIs the desired phase margin.
In a still further aspect of the present invention,
the second purpose of the invention is realized by the following technical scheme: a roll plate printing system is provided with a main station, a motor motion controller, a motor, an encoder, a coupler and a roll plate which are sequentially connected, and when the system operates in a closed loop, the parameters of the motor motion controller are designed by the parameter self-tuning method aiming at the roll plate printing system.
The third purpose of the invention is realized by the following technical scheme: a computing device comprising a processor and a memory for storing a processor executable program, the processor, when executing the program stored in the memory, implementing the method for self-tuning parameters for a flexographic printing system according to the first object of the present invention.
Compared with the prior art, the invention has the following advantages and effects:
(1) the invention relates to a parameter self-tuning method for a roll printing system, which comprises the steps of firstly, carrying out closed-loop identification and low-frequency correction by using a pseudorandom signal in the closed-loop operation process of the roll printing system so as to obtain a high-order mathematical model after low-frequency correction; then, obtaining disturbance distribution information by using the operation data and the model of the system and carrying out spectrum analysis on the disturbance distribution information to obtain a disturbance spectrum; and then, setting the parameters of the controller according to the disturbance frequency spectrum and the model, wherein the set parameters of the controller meet the requirements of the anti-interference capability and the stability of the system. The method is based on the closed-loop identification of the pseudo-random signal, the low-frequency correction and the self-tuning of the controller parameters based on the model and the interference, can design the controller with higher performance and stronger stability, solves the problems of high performance requirement, large system characteristic change and high order of a roll printing system, and is suitable for the roll printing system.
(2) The method inputs the pseudo-random signal as an excitation signal in the closed-loop operation, can excite the characteristics of each frequency band of the system, and then carries out modeling through the input and output signals, so as to obtain a high-order mathematical model capable of describing the characteristics of each frequency band of the system.
(3) The method disclosed by the invention performs information fusion by using steady-state information in the operation process and the model obtained by pseudo-random identification, and performs optimization correction on the pseudo-random identification process and the result, so that the low-frequency characteristic of the model is more accurate, and the accuracy of the model is further improved.
(4) The roll plate printing system can realize the self-tuning of the parameters of the controller, can meet the requirements of stability, tracking performance and anti-interference performance under different roll plate loads, has better system performance and is worthy of popularization.
Drawings
FIG. 1 is an overall flow chart of the parameter self-tuning method for a flexographic printing system of the present invention.
Fig. 2 is a flow chart of the closed loop identification in the method of fig. 1.
Fig. 3 is a schematic diagram of the configuration of the inventive rotogravure printing system.
Fig. 4 is a printing flow diagram of the system of fig. 3.
FIG. 5 is a time domain fit graph of the closed loop identification result and the measured output data.
FIG. 6 is a frequency domain fit graph of the closed loop identification result and the measured output data.
FIG. 7 is a comparison of a given position of the motor tracking S-shaped given position curve and an encoder measured position after tuning the controller.
Fig. 8 is a schematic diagram of position tracking error for the motor of fig. 7 tracking an S-shaped given position curve.
Detailed Description
The present invention will be described in further detail with reference to examples and drawings, but the present invention is not limited thereto.
Example 1
The embodiment discloses a parameter self-tuning method for a roll printing system, as shown in fig. 1, comprising the following steps:
s1, in the closed-loop operation process of the roll printing system, performing closed-loop identification and low-frequency correction by using a pseudo-random signal, thereby obtaining a high-order mathematical model after low-frequency correction, specifically as follows:
(1) as shown in fig. 2, the system is operated in a closed loop state by using a conservative controller, or the system is operated to a steady state by using a gain self-adjusting controller to obtain a stable but slightly conservative controller.
(2) And giving a pseudorandom excitation signal with a fixed length into a controllable input point close to the object to be identified in the loop, transmitting the superposed signal to the input of the object to be identified, and then acquiring input data and output data of the object to be identified according to a sampling period until the excitation of the pseudorandom signal is finished.
Compared with a step signal and a sine frequency sweep signal, the power distribution of the pseudo-random signal on each frequency band in the sampling frequency band is uniform, the length of the pseudo-random signal is short, the pseudo-random signal is an approximate white noise signal with constant power spectral density, and the characteristic of each frequency band of a system can be excited by inputting the pseudo-random signal as an excitation signal in closed-loop operation.
Under the requirement of self-tuning of the controller parameters, the object to be identified is a part of the system from the controller output end to the controller input end. In this example, the system is a part from the input end of the driver of the roll printing system to the middle of the speed output end of the encoder, and comprises the parts of the driver of the roll printing system, the motor of the roll printing system, the load of the motor, the encoder and an intermediate connecting link (coupler).
The input and output data u of the object to be recognized are the data u of the input and output ends of the object to be recognized after the pseudo-random excitation is superposedr(t)、yr(t)。
(3) Because the power distribution of the pseudo-random signals on each frequency band in the sampling frequency band is uniform, but the motor system is often influenced by low-frequency interference in the operation process, the low-frequency part of the model often has certain deviation from the actual part in the pseudo-random identification process, and whether the upper limit of the frequency of the interference signals can be estimated or not is judged firstly.
In a general case, for a roll printing system, the system interference dominant frequency can be roughly judged through mechanism analysis; or collecting a section of printing machine system position tracking error in a stable running state, carrying out Fourier spectrum analysis on the printing machine system position tracking error, and judging the main frequency band of system interference.
If not, the steady state data is the steady state value u input and output by the object to be identified when the system in the step (1) operates to the steady statesv、ysvInput/output data u with object to be recognizedr(t)、yr(t) carrying out data fusion, and identifying to obtain a high-order model after low-frequency correction:
will usvAnd ur(t) fusing to obtain u (t), and fusing ysvAnd yr(t) fusing to obtain y (t) such that:
u(jw)|w＝0＝usv；
u(jw)|w≠0＝ur(jw)；
y(jw)|w＝0＝ysv；
y(jw)|w≠0＝yr(jw)；
wherein u (jw), ur(jw)、y(jw)、yr(jw) are u (t), u, respectivelyr(t)、yr(t), y (t) Fourier frequency domain transform;
then, u (t), y (t) and u (t) obtained by fusion are used for identification.
If yes, obtaining an identification model capable of describing characteristics of each frequency band of the system through input and output data, and then carrying out low-frequency correction on the identification model to obtain a high-order mathematical model after low-frequency correction.
In this embodiment, the n-th order model transfer function g(s), i.e. the identification model, may be obtained by using a least square method or a subspace method according to the input and output data.
And performing low-frequency correction on the identification model, which specifically comprises the following steps:
(1) according to the input and output data u of the object to be identified in the steady statesv、ysvTo obtain the steady state gain of the system
(2) Low frequency separation is performed on the nth order model transfer function g(s) to reduce the amount of computation: g(s) ═ Gl(s)Gh(s) in which Gl(s) is the low frequency characteristic part of the system, Gh(s) is a system high frequency characteristic part;
(3) then solving the following formula to obtain a corrected system low-frequency characteristic part model Gl'(s)：
Wherein, w is a frequency variable,
refers to the frequency response, w, of the modelhEstimating the upper limit of the low-frequency interference frequency;
the above equations are various and can be solved, for example, by the least squares method. Get G by solutionl'(s) later, a corrected model G'(s) ═ G can be obtainedl'(s)Gh(s)。
S2, obtaining disturbance distribution information (disturbance signal) by using the operation data and model of the system, and carrying out spectrum analysis on the disturbance distribution information to obtain a disturbance spectrum;
s3, setting the controller parameters according to the disturbance frequency spectrum and the model, wherein the set controller parameters meet the requirements of the anti-interference capability and the stability of the system, and the process is as follows:
(1) and acquiring loop data in the running process in the stationary running stage, and acquiring a stationary stage interference estimation signal d (t) according to the controller and the model G'(s).
(2) Carrying out frequency domain transformation on the interference signal, determining frequency distribution and interference principal components, and obtaining an anti-interference capability index according to a performance index gamma and an interference channel model S:
|S(jw)d(jw)|<γ；
wherein S (jw) is the frequency response of interference channel S, S (jw) is S (S) non-volatile memorys＝jwAnd d (jw) is the Fourier frequency domain transform of d (t).
(3) Solving the corresponding parameters of the controller by using a loop forming method so as to:
wherein L (jw) is the system open loop transfer function,
for phase margin, Gm(. cndot.) is the margin of amplitude,
to expect amplitude margin, GrIs the desired phase margin. The desired margin is determined according to the operation requirement, and may be set to
The controller parameters meeting the above constraints can make the stability and tracking performance of the system reach the standard.
As shown in fig. 3, the roll printing system of the present embodiment has a master station, a motor motion controller, a motor and an encoder, a coupler, and a roll plate, which are connected in sequence, wherein the master station issues a motion command to the motor motion controller through a bus, the electrode motion controller issues a control signal to the motor and the encoder, the encoder feeds back a roll plate running state to the motor motion controller in real time, and the motor motion controller uploads the running state to the master station.
The printing process of the system is shown in fig. 4: (1) before printing, each part is powered off, a roll plate is replaced, and feeding and electrifying are carried out; (2) the motors stably run at low speed, the motion controllers of the motors are in a synchronous state, the parameter self-tuning method is applied to design the controller parameters meeting the requirements of anti-interference capability and stability during high-speed running, and the controller parameters are mixed, so that the performance requirement is avoided at the stage and the operation lasts for 30 minutes; (3) the performance requirements at this stage are high, as the motors run at high speed and printing begins.
Fig. 5 is a time domain fitting graph of the closed-loop identification result and the actual measurement output data, the actual measurement input and output data of the object to be identified are collected, the input data is used as the input of the identification model, the output of the identification model is calculated, and the model output (dotted line) and the actual measurement output (solid line) are compared in the time domain. Fig. 6 is a frequency domain fitting graph of the closed-loop identification result and the actually measured output data, the actually measured input and output data of the object to be identified is used for performing spectrum analysis, and the spectral division result (solid line) and the identification result (dotted line) are compared with a bode graph. As shown in fig. 5 and 6, the solid line and the dotted line substantially coincide with each other, which shows that the model is accurate and can be applied to a system with a high order and a large load variation, such as a roll printing system.
Fig. 7 is a comparison graph of the S-shaped given position curve traced by the printing system motor after the controller is set, the given position (dotted line) and the actual measurement position (solid line) of the encoder, as can be seen from fig. 7, the two curves are superposed, fig. 8 is a position tracing error of the corresponding S-shaped given position curve traced by the printing system motor, as can be seen from fig. 8, the actual measurement error is generally within plus and minus 2 filaments in a steady state, but the system requirement error does not exceed plus and minus 10 filaments, and it can be seen that the system of the embodiment can meet the performance requirement.
Example 2
The embodiment discloses a computing device, which includes a processor and a memory for storing a processor executable program, and when the processor executes the program stored in the memory, the method for self-tuning the parameters of the roll printing system described in embodiment 1 is implemented, specifically as follows:
in the closed-loop operation process of the roll printing system, performing closed-loop identification and low-frequency correction by using a pseudorandom signal so as to obtain a high-order mathematical model after low-frequency correction;
obtaining disturbance distribution information by using the operation data and the model of the system and carrying out spectrum analysis on the disturbance distribution information to obtain a disturbance spectrum;
and (4) setting the controller parameters according to the disturbance frequency spectrum and the model, wherein the set controller parameters meet the requirements of the anti-interference capability and the stability of the system.
The computing device described in this embodiment may be a desktop computer, a notebook computer, a smart phone, a PDA handheld terminal, a tablet computer, or other terminal device with a processor function.
The above embodiments are preferred embodiments of the present invention, but the present invention is not limited to the above embodiments, and any other changes, modifications, substitutions, combinations, and simplifications which do not depart from the spirit and principle of the present invention should be construed as equivalents thereof, and all such changes, modifications, substitutions, combinations, and simplifications are intended to be included in the scope of the present invention.
Claims (10)
1. A parameter self-tuning method for a roll printing system is characterized by comprising the following steps:
in the closed-loop operation process of the roll printing system, performing closed-loop identification and low-frequency correction by using a pseudorandom signal so as to obtain a high-order mathematical model after low-frequency correction;
obtaining disturbance distribution information by using the operation data and the model of the system and carrying out spectrum analysis on the disturbance distribution information to obtain a disturbance spectrum;
and (4) setting the controller parameters according to the disturbance frequency spectrum and the model, wherein the set controller parameters meet the requirements of the anti-interference capability and the stability of the system.
2. The method of claim 1, wherein the closed-loop identification and low-frequency correction are performed using a pseudo-random signal, so as to obtain a low-frequency corrected higher-order mathematical model as follows:
(1) a conservative controller is used for enabling the system to be in a closed-loop operation state, or a gain self-adjusting controller is used for obtaining a stable but slightly conservative controller, so that the system stably operates to a stable state;
(2) giving a pseudorandom excitation signal with a fixed length to a controllable input point close to an object to be identified in a loop, transmitting a superposed signal to the input of the object to be identified, and then acquiring input data and output data of the object to be identified according to a sampling period until the excitation of the pseudorandom signal is finished;
(3) judging whether the upper limit of the frequency of the interference signal can be estimated or not, if not, performing data fusion on the steady-state data and the input and output data of the object to be identified, and identifying to obtain a high-order model after low-frequency correction;
if yes, obtaining an identification model capable of describing characteristics of each frequency band of the system through input and output data, and then carrying out low-frequency correction on the identification model to obtain a high-order mathematical model after low-frequency correction.
3. The method for self-tuning parameters of a roll printing system according to claim 2, wherein the object to be identified is a part of the system from the controller output to the controller input; the input and output data u of the object to be identified are superposed with the pseudo-random excitation signalr(t)、yr(t)。
4. The method for self-tuning parameters of a roll printing system according to claim 3, wherein the steady state data is a steady state value u of the input and output of the object to be recognized when the system is operated to a steady state in step (1)svAnd ysv；
Performing data fusion on the steady-state data and the input and output data of the object to be identified, and identifying to obtain a high-order model after low-frequency correction, wherein the method specifically comprises the following steps:
will usvAnd ur(t) fusing to obtain u (t), and fusing ysvAnd yr(t) fusing to obtain y (t) such that:
u(jw)|w＝0＝usv；
u(jw)|w≠0＝ur(jw)；
y(jw)|w＝0＝ysv；
y(jw)|w≠0＝yr(jw)；
wherein u (jw), ur(jw)、y(jw)、yr(jw) are u (t), u, respectivelyr(t)、yr(t), y (t) Fourier frequency domain transform;
then, u (t), y (t) and u (t) obtained by fusion are used for identification.
5. The method for parameter self-tuning for a flexographic printing system according to claim 2, characterized in that the acquisition of the identification model is in particular: and obtaining an n-order model transfer function G(s) by using a least square method or a subspace method according to the input and output data.
6. The method of claim 5, wherein the identification model is low frequency corrected, as follows:
(1) according to the input and output data u of the object to be identified in the steady statesv、ysvTo obtain the steady state gain of the system
(2) Low frequency separation is performed on the nth order model transfer function g(s) to reduce the amount of computation: g(s) ═ Gl(s)Gh(s) in which Gl(s) is the low frequency characteristic part of the system, Gh(s) is a system high frequency characteristic part;
(3) then solve the following:
Gl'(0)＝K；
min|Gl'(jw)-Gl(jw)|,w>wh；
wherein w is a frequency variable, Gl'(0)＝Gl'(s)|s＝0，Gl(jw)＝Gl(s)|s＝jw，Gl'(jw)＝Gl'(s)|s＝jwRefers to the frequency response, w, of the modelhEstimating the upper limit of the low-frequency interference frequency;
obtaining G from the above formulal'(s) to obtain a corrected model G'(s) ═ Gl'(s)Gh(s)。
7. The method of claim 1, wherein the controller parameter tuning is performed according to a disturbance spectrum and a model, and the process is as follows:
(1) acquiring loop data in operation in a stable operation stage, and acquiring a stable stage interference estimation signal d (t) according to a controller and a model G'(s);
(2) carrying out frequency domain transformation on the interference signal, determining frequency distribution and interference principal components, and obtaining an anti-interference capability index according to a performance index gamma and an interference channel model S:
|S(jw)d(jw)|<γ；
wherein S (jw) is the frequency response of interference channel S, S (jw) is S (S) non-volatile memorys＝jwD (jw) is the Fourier frequency domain transform of d (t);
(3) solving the corresponding parameters of the controller by using a loop forming method so as to:
|S(jw)d(jw)|<γ；
|Gm(L(jw))>Gr|；
wherein L (jw) is the system open loop transfer function,
for phase margin, Gm(. cndot.) is the margin of amplitude,
to expect amplitude margin, GrIs the desired phase margin.
8. The method for parameter self-tuning for a flexographic printing system according to claim 7,
Gr＝5db。
9. a roll printing system, characterized in that the roll printing system comprises a master station, a motor motion controller, a motor and an encoder, a coupler and a roll plate which are connected in sequence, and when the system operates in a closed loop, the parameters of the motor motion controller are designed by the parameter self-tuning method for the roll printing system as claimed in any one of claims 1 to 8.
10. A computing device comprising a processor and a memory for storing a processor-executable program, wherein the processor, when executing the program stored in the memory, implements the method for parameter self-tuning for a flexographic printing system of any of claims 1 to 8.
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